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Visibility Modeling and Prediction for Free Space Optical Communication Systems for South Africa


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DOI: https://doi.org/10.15866/irecap.v10i3.18008

Abstract


Due to the cost and complexity in the measurement of Free Space Optical (FSO) visibility, this paper presents regression models based on meteorological factors to reliably estimate atmospheric visibility. The meteorological factors used are relative humidity, temperature, fractional sunshine, atmospheric pressure and wind speed for Cape Town, South Africa. Initially, Simple Linear Regression (SLR) models are developed and presented. To improve the performance of the regression, the SLR model is extended to a Multiple Linear Regression model (MLR) where three of the meteorological factors are taken into consideration simultaneously. It was found that by implementing MLR, the model performance improves considerably. However, it was also found that the model had effects of multicollinearity due to some of the predictor variables being highly correlated. To mitigate the effects of multicollinearity, two approaches are proposed, 1) removing the problematic terms from the regression model and 2) introducing interaction terms. Both approaches are seen to have little impact on the overall performance of the MLR model while the estimated model coefficients are significant at 5% significant level. In general, it is found through application of standard statistical tests that both SLR and MLR models can be used adequately to determine visibility at a location.
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Keywords


Free Space Optics; Visibility; Regression; Correlation Matrix; Multicollinearity; Variance Inflation Factor

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References


C. Yu, L. Yu, Y. Wu, Y. He, and Q. Lu, Uplink scheduling and link adaptation for narrowband Internet of Things systems, IEEE Access, Volume 5, February 2017, Pages 1724-1734.
https://doi.org/10.1109/access.2017.2664418

I. Alimi, A. Shahpari, V. Ribeiro, N. Kumar, P. Monteiro, and A. Teixeira, Optical wireless communication for future broadband access networks, 2016 21st European conference on networks and optical communications (NOC), pp. 124-128, Lisbon, Portugal, June 2016.
https://doi.org/10.1109/noc.2016.7506998

G. Parca, A. Tavares, A. Shahpari, A. Teixeira, V. Carrozzo, and G. T. Beleffi, FSO for broadband multi service delivery in future networks, 2013 2nd International Workshop on Optical Wireless Communications (IWOW), pp. 67-70, Newcastle upon Tyne, UK, October 2013.
https://doi.org/10.1109/iwow.2013.6777779

Z. Ghassemlooy, W. Popoola, and S. Rajbhandari, Optical wireless communications: system and channel modelling with Matlab® (CRC press, 2019).
https://doi.org/10.1201/9781315151724

Ceruti, A., Bombardi, T., Piancastelli, L., Visual Flight Rules Pilots Into Instrumental Meteorological Conditions: a Proposal for a Mobile Application to Increase In-flight Survivability, (2016) International Review of Aerospace Engineering (IREASE), 9 (5), pp. 144-151.
https://doi.org/10.15866/irease.v9i5.10391

A. Usman, G. Ismaila, K. Olaore, and S. Lawal, Developing a model for predicting the visibility for Sokoto using fraction of sunshine hours data, Research Journal of Applied Sciences, Volume 6, (Issue 6), 2011, Pages 378-380.
https://doi.org/10.3923/rjasci.2011.378.380

A. Usman, K. Olaore, and G. Ismaila, Estimating visibility using some Meteorological data at Sokoto, Nigeria, Int. J. Basic Appli. Sci, Volume. 1, (Issue 4), April 2013, Pages 810-815.

D. Akpootu, M. Iliyasu, W. Mustapha, S. Aruna, and S. Yusuf, Developing Regression Models for Estimating Atmospheric Visibility over Ikeja, Nigeria, Journal of Scientific Research and Reports, Volume 15, (Issue 6), September 2017, Pages 1-14.
https://doi.org/10.9734/jsrr/2017/36670

Balamurugan, S., Alwarsamy, T., Boring Tool Chatter Suppression Using Magneto-Rheological Fluid Damper through Regression Models, (2013) International Review of Mechanical Engineering (IREME), 7 (3), pp. 556-562.

Deb, T., Kumar Pal, S., Study on Uplift Behavior of Single Belled Anchor Piles in Sand Bed and Multiple Regression Analyses, (2017) International Review of Civil Engineering (IRECE), 8 (3), pp. 97-112.
https://doi.org/10.15866/irece.v8i3.12001

Idroes, R., Noviandy, T., Maulana, A., Suhendra, R., Sasmita, N., Muslem, M., Idroes, G., Irvanizam, I., Retention Index Prediction of Flavor and Fragrance by Multiple Linear Regression and the Genetic Algorithm, (2019) International Review on Modelling and Simulations (IREMOS), 12 (6), pp. 373-380.
https://doi.org/10.15866/iremos.v12i6.18353

Jai Aultrin, K., Anand, M., Optimization of Machining Parameters in AWJM Process for Lead Tin Alloy Using RSM and Regression Analysis, (2015) International Review of Mechanical Engineering (IREME), 9 (2), pp. 136-144.
https://doi.org/10.15866/ireme.v9i2.4791

Thanga Parvathi, B., MercyShalinie, S., Differential Evolution (DE) based Multiple Regression Model for Classification, (2014) International Review on Computers and Software (IRECOS), 9 (6), pp. 1117-1124.

E. Kinab, T. Salem, and G. Merhy, BIPV building integrated photovoltaic systems in mediterranean climate, International Conference on Renewable Energies for Developing Countries 2014, pp. 180-185, Beirut, Lebanon, November 2014.
https://doi.org/10.1109/redec.2014.7038553

M. Sanz, A. Carrara, C. Gimeno, A. Bucher, and R. Lopez, Effects of a dry and warm summer conditions on CO2 and energy fluxes from three Mediterranean ecosystems, Geophys. Res. Abstr, Volume 6, 2004, Page 3239.

T. Silva, R. Vicente, F. Rodrigues, A. Samagaio, and C. Cardoso, Performance of a window shutter with phase change material under summer Mediterranean climate conditions, Applied Thermal Engineering, Volume 84, June 2015, Pages 246-256.
https://doi.org/10.1016/j.applthermaleng.2015.03.059

E. Xoplaki, J. F. González-Rouco, J. Luterbacher, and H. Wanner, Mediterranean summer air temperature variability and its connection to the large-scale atmospheric circulation and SSTs, Climate dynamics, Volume 20, (Issue 7-8), March 2003, Pages 723-739.
https://doi.org/10.1007/s00382-003-0304-x

G. James, D. Witten, T. Hastie, and R. Tibshirani, An introduction to statistical learning (Springer-Verlag New York, 2013).

S. Sheather, A modern approach to regression with R (Springer-Verlag New York, 2009).

M. H. Kutner, C. J. Nachtsheim, J. Neter, and W. Li, Applied linear statistical models (McGraw-Hill Irwin New York, 2005).

M. Jarraud, Guide to meteorological instruments and methods of observation, World Meteorological Organisation (WMO), Geneva, Switzerland, Volume 1, (Issue 8), 2008, Page 29.

A. Prokes, Atmospheric effects on availability of free space optics systems, Optical Engineering, Volume 48, (Issue 6), June 2009, Page 066001.
https://doi.org/10.1117/1.3155431

Al-Adwany, M., Yahya, H., Thanoon, M., Hamdoon, H., Saadallah, N., Hamed, A., Simulation and Hardware Implementation of DC-Biased Optical OFDM (DCO-OFDM) for Visible Light Communications, (2020) International Review on Modelling and Simulations (IREMOS), 13 (2), pp. 108-117.
https://doi.org/10.15866/iremos.v13i2.17486

Cárdenas, J., Valencia, G., Forero, J., Hydraulic Performance Prediction Methodology in Regenerative Pumps Through CFD Analysis, (2019) International Journal on Energy Conversion (IRECON), 7 (6), pp. 253-262.
https://doi.org/10.15866/irecon.v7i6.18341


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